| // inverse_chi_squared_distribution_find_df_example.cpp |
| |
| // Copyright Paul A. Bristow 2010. |
| // Copyright Thomas Mang 2010. |
| |
| // Use, modification and distribution are subject to the |
| // Boost Software License, Version 1.0. |
| // (See accompanying file LICENSE_1_0.txt |
| // or copy at http://www.boost.org/LICENSE_1_0.txt) |
| |
| //#define BOOST_MATH_INSTRUMENT |
| |
| // Example 1 of using inverse chi squared distribution |
| #include <boost/math/distributions/inverse_chi_squared.hpp> |
| using boost::math::inverse_chi_squared_distribution; // inverse_chi_squared_distribution. |
| using boost::math::inverse_chi_squared; //typedef for nverse_chi_squared_distribution double. |
| |
| #include <iostream> |
| using std::cout; using std::endl; |
| #include <iomanip> |
| using std::setprecision; |
| using std::setw; |
| #include <cmath> |
| using std::sqrt; |
| |
| int main() |
| { |
| cout << "Example using Inverse chi squared distribution to find df. " << endl; |
| try |
| { |
| cout.precision(std::numeric_limits<double>::max_digits10); // |
| int i = std::numeric_limits<double>::max_digits10; |
| cout << "Show all potentially significant decimal digits std::numeric_limits<double>::max_digits10 = " << i << endl; |
| |
| cout.precision(3); |
| double nu = 10.; |
| double scale1 = 1./ nu; // 1st definition sigma^2 = 1/df; |
| double scale2 = 1.; // 2nd definition sigma^2 = 1 |
| inverse_chi_squared sichsq(nu, 1/nu); // Explicitly scaled to default scale = 1/df. |
| inverse_chi_squared ichsq(nu); // Implicitly scaled to default scale = 1/df. |
| // Try degrees of freedom estimator |
| |
| //double df = chi_squared::find_degrees_of_freedom(-diff, alpha[i], alpha[i], variance); |
| |
| cout << "ichsq.degrees_of_freedom() = " << ichsq.degrees_of_freedom() << endl; |
| |
| double diff = 0.5; // difference from variance to detect (delta). |
| double variance = 1.; // true variance |
| double alpha = 0.9; |
| double beta = 0.9; |
| |
| cout << "diff = " << diff |
| << ", variance = " << variance << ", ratio = " << diff/variance |
| << ", alpha = " << alpha << ", beta = " << beta << endl; |
| using boost::math::detail::inverse_chi_square_df_estimator; |
| using boost::math::policies::default_policy; |
| inverse_chi_square_df_estimator<> a_df(alpha, beta, variance, diff); |
| |
| cout << "df est" << endl; |
| for (double df = 1; df < 3; df += 0.1) |
| { |
| double est_df = a_df(1); |
| cout << df << " " << a_df(df) << endl; |
| } |
| |
| //template <class F, class T, class Tol, class Policy>std::pair<T, T> |
| // bracket_and_solve_root(F f, const T& guess, T factor, bool rising, Tol tol, boost::uintmax_t& max_iter, const Policy& pol) |
| |
| |
| //double df = inverse_chi_squared_distribution<>::find_degrees_of_freedom(diff, alpha, beta, variance, 0); |
| |
| double df = inverse_chi_squared::find_degrees_of_freedom(diff, alpha, beta, variance, 100); |
| |
| cout << df << endl; |
| } |
| catch(const std::exception& e) |
| { // Always useful to include try & catch blocks because default policies |
| // are to throw exceptions on arguments that cause errors like underflow, overflow. |
| // Lacking try & catch blocks, the program will abort without a message below, |
| // which may give some helpful clues as to the cause of the exception. |
| std::cout << |
| "\n""Message from thrown exception was:\n " << e.what() << std::endl; |
| } |
| return 0; |
| } // int main() |
| |
| /* |
| |
| Output is: |
| |
| Example using Inverse chi squared distribution to find df. |
| Show all potentially significant decimal digits std::numeric_limits<double>::max_digits10 = 17 |
| 10 |
| |
| Message from thrown exception was: |
| Error in function boost::math::inverse_chi_squared_distribution<double>::inverse_chi_squared_distribution: Degrees of freedom argument is 1.#INF, but must be > 0 ! |
| diff = 0.5, variance = 1, ratio = 0.5, alpha = 0.1, beta = 0.1 |
| df est |
| 1 1 |
| ratio+1 = 1.5, quantile(0.1) = 0.00618, cdf = 6.5e-037, result = -0.1 |
| 1.1 -0.1 |
| ratio+1 = 1.5, quantile(0.1) = 0.00903, cdf = 1.2e-025, result = -0.1 |
| 1.2 -0.1 |
| ratio+1 = 1.5, quantile(0.1) = 0.0125, cdf = 8.25e-019, result = -0.1 |
| 1.3 -0.1 |
| ratio+1 = 1.5, quantile(0.1) = 0.0166, cdf = 2.17e-014, result = -0.1 |
| 1.4 -0.1 |
| ratio+1 = 1.5, quantile(0.1) = 0.0212, cdf = 2.2e-011, result = -0.1 |
| 1.5 -0.1 |
| ratio+1 = 1.5, quantile(0.1) = 0.0265, cdf = 3e-009, result = -0.1 |
| 1.6 -0.1 |
| ratio+1 = 1.5, quantile(0.1) = 0.0323, cdf = 1.11e-007, result = -0.1 |
| 1.7 -0.1 |
| ratio+1 = 1.5, quantile(0.1) = 0.0386, cdf = 1.7e-006, result = -0.1 |
| 1.8 -0.1 |
| ratio+1 = 1.5, quantile(0.1) = 0.0454, cdf = 1.41e-005, result = -0.1 |
| 1.9 -0.1 |
| ratio+1 = 1.5, quantile(0.1) = 0.0527, cdf = 7.55e-005, result = -0.1 |
| 2 -0.1 |
| ratio+1 = 1.5, quantile(0.1) = 0.0604, cdf = 0.000291, result = -0.1 |
| 2.1 -0.1 |
| ratio+1 = 1.5, quantile(0.1) = 0.0685, cdf = 0.00088, result = -0.1 |
| 2.2 -0.1 |
| ratio+1 = 1.5, quantile(0.1) = 0.0771, cdf = 0.0022, result = -0.0999 |
| 2.3 -0.0999 |
| ratio+1 = 1.5, quantile(0.1) = 0.0859, cdf = 0.00475, result = -0.0997 |
| 2.4 -0.0997 |
| ratio+1 = 1.5, quantile(0.1) = 0.0952, cdf = 0.00911, result = -0.0993 |
| 2.5 -0.0993 |
| ratio+1 = 1.5, quantile(0.1) = 0.105, cdf = 0.0159, result = -0.0984 |
| 2.6 -0.0984 |
| ratio+1 = 1.5, quantile(0.1) = 0.115, cdf = 0.0257, result = -0.0967 |
| 2.7 -0.0967 |
| ratio+1 = 1.5, quantile(0.1) = 0.125, cdf = 0.039, result = -0.094 |
| 2.8 -0.094 |
| ratio+1 = 1.5, quantile(0.1) = 0.135, cdf = 0.056, result = -0.0897 |
| 2.9 -0.0897 |
| ratio+1 = 1.5, quantile(0.1) = 20.6, cdf = 1, result = 0.9 |
| |
| ichsq.degrees_of_freedom() = 10 |
| diff = 0.5, variance = 1, ratio = 0.5, alpha = 0.9, beta = 0.9 |
| df est |
| 1 1 |
| ratio+1 = 1.5, quantile(0.9) = 0.729, cdf = 0.269, result = -0.729 |
| 1.1 -0.729 |
| ratio+1 = 1.5, quantile(0.9) = 0.78, cdf = 0.314, result = -0.693 |
| 1.2 -0.693 |
| ratio+1 = 1.5, quantile(0.9) = 0.83, cdf = 0.36, result = -0.655 |
| 1.3 -0.655 |
| ratio+1 = 1.5, quantile(0.9) = 0.879, cdf = 0.405, result = -0.615 |
| 1.4 -0.615 |
| ratio+1 = 1.5, quantile(0.9) = 0.926, cdf = 0.449, result = -0.575 |
| 1.5 -0.575 |
| ratio+1 = 1.5, quantile(0.9) = 0.973, cdf = 0.492, result = -0.535 |
| 1.6 -0.535 |
| ratio+1 = 1.5, quantile(0.9) = 1.02, cdf = 0.534, result = -0.495 |
| 1.7 -0.495 |
| ratio+1 = 1.5, quantile(0.9) = 1.06, cdf = 0.574, result = -0.455 |
| 1.8 -0.455 |
| ratio+1 = 1.5, quantile(0.9) = 1.11, cdf = 0.612, result = -0.417 |
| 1.9 -0.417 |
| ratio+1 = 1.5, quantile(0.9) = 1.15, cdf = 0.648, result = -0.379 |
| 2 -0.379 |
| ratio+1 = 1.5, quantile(0.9) = 1.19, cdf = 0.681, result = -0.342 |
| 2.1 -0.342 |
| ratio+1 = 1.5, quantile(0.9) = 1.24, cdf = 0.713, result = -0.307 |
| 2.2 -0.307 |
| ratio+1 = 1.5, quantile(0.9) = 1.28, cdf = 0.742, result = -0.274 |
| 2.3 -0.274 |
| ratio+1 = 1.5, quantile(0.9) = 1.32, cdf = 0.769, result = -0.242 |
| 2.4 -0.242 |
| ratio+1 = 1.5, quantile(0.9) = 1.36, cdf = 0.793, result = -0.212 |
| 2.5 -0.212 |
| ratio+1 = 1.5, quantile(0.9) = 1.4, cdf = 0.816, result = -0.184 |
| 2.6 -0.184 |
| ratio+1 = 1.5, quantile(0.9) = 1.44, cdf = 0.836, result = -0.157 |
| 2.7 -0.157 |
| ratio+1 = 1.5, quantile(0.9) = 1.48, cdf = 0.855, result = -0.133 |
| 2.8 -0.133 |
| ratio+1 = 1.5, quantile(0.9) = 1.52, cdf = 0.872, result = -0.11 |
| 2.9 -0.11 |
| ratio+1 = 1.5, quantile(0.9) = 29.6, cdf = 1, result = 0.1 |
| |
| |
| */ |
| |